Virtual Seminar

Modern Data Warehousing Fundamentals

December 5, 9:00am PT/12:00pm ET

Meet analytics demands across the business

Explore new trends and use cases in data warehousing, including exploration and discovery, self-service ad-hoc analysis, predictive analytics, and additional ways to get deeper insight from all your data, regardless of where it lives.

Modern Data Warehousing Fundamentals will discuss ways to mitigate the limitations of legacy data warehouses with strategies to modernize your data warehouse architecture and infrastructure that benefit both traditional analytics practitioners and data scientists and engineers.

Topics to be covered include:

Challenges of traditional architectures to address modern demands and the benefits of a modern data warehouse

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12/05/2018 9:00 AM12/05/2018 12:00 PMAmerica/Los_AngelesModern Data Warehousing Fundamentals Virtual EventExplore new trends and use cases in data warehousing including exploration and discovery, self-service ad-hoc analysis, predictive analytics and more ways to get deeper business insight. Modern Data Warehousing Fundamentals will show how to modernize your data warehouse architecture and infrastructure for benefits to both traditional analytics practitioners and data scientists and engineers.
Virtual Event

Agenda

Part I: Introducing the Modern Data Warehouse: Challenges, Use Cases, and Opportunities

Today’s businesses demand more insight, faster, from higher volumes and variety of data. The modern data warehouse is designed to handle these new challenges, using new architectures based on new technologies. In this session we will explore:

Use cases for modern data warehousing, including data science, data engineering, and machine learning

Part II: Exploring the Move to Cloud and Maintaining a Common Data Context

The cloud offers a great advantage in time to delivery for new analytics projects, flexibility in scaling up and down based on need, and more. However, moving to the cloud, in whole or in part, has challenges, especially around maintaining a consistent data context for security, governance, and metadata. In this session we will explore:

Opportunities offered by data warehousing in the cloud

Use cases for data warehousing in the cloud

Technologies, architectures, and tools to help maintain a shared data experience when using pure or hybrid cloud deployment models

Part III: Healthy in Production: Optimizing, Managing, and Troubleshooting

The modern data warehouse is a myriad of new technologies working together to provide better insight on more data. This new architecture comes complete with new challenges for keeping things running smoothly. This session will explore:

New challenges in data warehouse optimization

New challenges in data warehouse troubleshooting

Tools and techniques to manage, optimize, and troubleshoot all manner of workloads

Speakers

Director of Product Management

Eva Nahari

Eva is a director of product management on Cloudera’s Data Warehouse product team, with a focus on discovery data warehouse use cases and end-user experience. Eva brings broad and deep insight into cross-industry data strategies and customer success based on her many years of experience in modern data warehousing and as the chair of Cloudera Executive Advisory Board. Before Cloudera, she spent 15+ years in infrastructure software. Eva has an M.Sc. in computer science, with focus on AI, machine learning, and autonomous systems. She has been awarded multiple technical patents throughout her career.

Director of Product Management

Greg Rahn

Greg is responsible for driving SQL product strategy as director of product management on Cloudera’s Data Warehouse product team, including working directly with Impala. Greg has spent more than 20 years working with relational database systems across a variety of roles—including software engineering, database administration, database performance engineering, and most recently product management—providing a holistic view and expertise on the database market. Previously, Greg was part of the esteemed Real-World Performance Group at Oracle and was the first member of the product management team at Snowflake Computing.

Senior Product Manager

Santosh Kumar

Santosh leads Cloudera's metadata initiative, Shared Data Experience (SDX), and, as part of Cloudera's Data Warehouse product team, is responsible for the SQL-on-Hadoop components of Cloudera’s stack, including Hive and Pig. Before joining Cloudera, he worked in analytics at Facebook and engineering at Yahoo and Akamai. He received his BS in computer science from IIT Kanpur, India, and an MBA from Insead, France.

Software Engineer, Impala

Alan Choi

Alan Choi is a software engineer at Cloudera working on the Impala project. Before joining Cloudera, he worked at Greenplum on the Greenplum-Hadoop integration. Prior to that, Alan worked extensively on Pl/SQL and SQL at Oracle and co-authored the Oracle White Paper "Integrating Hadoop Data with Oracle Parallel Processing," which was published in January 2010.

Product Manager

Raman Rajasekhar

Raman is a product manager on Cloudera’s Data Warehouse product team, specializing in building machine learning, predictive analytics, and data management products. He has a passion for creating and implementing high-performance algorithms for massively parallel processing and big data platforms. Raman has more than 15 years of international experience in R&D, product development, data science and machine learning, and engineering, with a deep understanding of healthcare, financial, and high-tech manufacturing domains.

Director, Product Marketing

David Dichmann

David is director of product marketing marketing for Cloudera Data Warehouse. He has more than 25 years experience in information architecture and enterprise architecture, turning data into information to help businesses and people make an informed decision. Before joining Cloudera, David worked for companies like Sybase, SAP, and Hewlett Packard Enterprise. David has been published in industry magazines and is a regular speaker at industry events.